Python · MIT
recommenders-team/recommenders
Best Practices on Recommendation Systems
★ 22k
Stars
3.3k forks · 184 open issues
+5.0/wk
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
32.1
Momentum / 100
see the breakdown below
8y ago
Created
last push 2d ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 4.5 | +5.0/wk, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 0.0 | last week ran 0.50× the monthly pace |
| Freshness | 15 | 15.0 | last push 2d ago; decays to zero at 180 days |
| Scale | 15 | 12.6 | 22k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 32.1 | sum of the above |
Detail
| Topics | aiartificial-intelligencedata-sciencedeep-learningjupyter-notebookkubernetesmachine-learningoperationalizationpythonrankingratingrecommendationrecommendation-algorithmrecommendation-enginerecommendation-systemrecommendertutorial |
| Matched on | Dev Tools (kubernetes) Learning & Roadmaps (tutorial) |
| Short window | +5 stars over 7 days = 0.7/day |
| Long window | +37 stars over 26 days = 1.4/day |
| Lifetime average | 7.40 stars/day over 2,969 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |